The Computing Method And Application Of Nonlinear Mixed Effects Models For Repeated Measures Data

In recent years, scholars propose a general, nonlinear mixed effects model for repeatedmeasures data and define estimators for its parameters. The proposed estimators are a naturalcombination of least squares estimators for nonlinear fixed effects models and maximumlikelihood(or restricted maximum likelihood)estimators for nonlinear fixed effects models.The thesis implement New-Raphson estimation using previously developed computationalmethods for nonlinear fixed effects models and for linear mixed effects models.Two examplesare presented and the connections between this work and recent work on generalized linearmixed effects models are discussed.（1）It introduces the relevant knowledge of the development and applications on therepeated measures data and nonlinear mixed effects model.（2）It studies characteristic of repeated measures data, and using the likelihoodestimator.（3）It studies the application of the model of the inter individual and intra individualvariation in, also consider the nonlinear parameters, allowing the fixed effects and mixedeffects in the linear part, so you can easily analyze the unbalanced data such as randommissing data.（4）The nonlinear mixed effect with repeated measurements, which applied in exampleeight guinea pig tissue samples with different concentrations of b-methyl glucoside, drawrelevant conclusions.